Key result
AIM ECG-AI trial tests whether AI decision support improves detection of LVEF ≤40% versus usual care.
Why the study?
While clinical studies have evaluated ECG-AI algorithms, multicenter data evaluating the clinical impact of an EHR-integrated, point-of-care CDSS delivering ECG-AI results during routine outpatient care were needed.
Does an EHR-integrated ECG-AI clinical decision support software improve the detection of left ventricular ejection fraction ≤40% in adult patients with no history of low LVEF?
Population
>32,000 eligible clinical encounters with adult patients with no history of low LVEF and a documented digital ECG
Comparison
EHR-integrated point-of-care CDSS access vs usual care
Design
Multicenter cluster-randomized trial
Follow-up
90 day
Authors
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This paper outlines the design of a multicenter, cluster-randomized trial evaluating an EHR-integrated ECG-AI clinical decision support system for detecting low LVEF in routine outpatient care.
RCT (n=32,000)
Cluster-randomized
Yes
Does an EHR-integrated ECG-AI clinical decision support software improve the detection of left ventricular ejection fraction ≤40% in adult patients with no history of low LVEF?
This paper outlines the design of a multicenter, cluster-randomized trial evaluating an EHR-integrated ECG-AI clinical decision support system for detecting low LVEF in routine outpatient care.
López-Jiménez et al. (2025) conducted an RCT in Low left ventricular ejection fraction (LVEF) (n=32,000). ECG-AI-Based Clinical Decision Support Software (CDSS) vs. Usual care was evaluated on Detection of left ventricular ejection fraction ≤40 % by echocardiography. The AIM ECG-AI trial is a multicenter, cluster-randomized study designed to evaluate whether an ECG-AI-based clinical decision support software improves the detection of LVEF ≤40% versus usual care.
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